How fast does Labview perform integer, float and matrix calculations?

Question

What is the speed of a modern CPU? Ok it is 3Ghz, one to four cores etc. but how much work can I get done in one clock cycle at this speed?
This kind of questions have been in the back of my head for some time, so I decided to test it. Of course using Labview since it so easy to to use!
I wrote a really simple program that performed 10000 adds 3 to an 32 bit integer in a loop. It then repeats this until 1000ms has elapsed and calculates the MegaInts (or whatever I should call it). I then did the same thing by adding 3 to a matrix of 10000 32bit ints.
On and dual core 3Ghz PC from 2005 I got 261 Mints in a loop, and 1400 Mints in matrix. Only one core seems to be used, CPU load aorund 50%. So every two clock cycles or so I get some work done in a matrix calculation. Also older 1,8Ghz Celeron computers performs about the same in this test, even though they feel very slow in normal use.
On a newer 4/8 core 2,8Ghz PC from this year I got 830 Mints in a loop, and 5900 Mints in matrix. Only one core seems to be used, CPU load aorund 12%. So actually more than one add per clock cycle!
This indicates that either the compiler is smarter than me and does not to all integer adds, or the CPU is smart and do them very fast!
See this as not the complete benchmark of Labview in integer, float and matrix calculations, but as a teaser to make you do your own tests.
Play around and have fun!

Answer 1

Norbert_B wrote:
Yamaeda wrote:
A standard loop only runs in 1 thread,[...]
That is not true.
A standard loop follows the clumping algorithm during compilation. Clumps can be distributed on any number of threads.
So, a standard loop CAN be distributed between several threads.
There are, however, some settings and structures which will result in a single thread per loop:
- Setting the calling VI to "subroutine" priority (not recommended)
- Using a Timed Loop instead of a standard one
- AFAIK: Containing the loop in an InPlace Element Structure with "Data Value Reference" border nodes
There is at least one additional option, but it is so unlikely (as it messes up with most of LV!) that i will not point it out here.....
Norbert
Why would we have parallellization options for a loop if it's already multithreaded? I'd love if loops would automatically parallellize.
If you mean the content inside the loop, then it'll follow ordinary optimization and use several threads if possible. In this case OP mentioned 1 cpu was at 100%.
/Y
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